docstr: ivy.Array instance method variant of ivy.dct. This method simply
  wraps the function, and so the docstring for ivy.dct also applies to
  this method with minimal changes.
  
  Parameters
  ----------
  self
      The input signal.
  type
      The type of the dct. Must be 1, 2, 3 or 4.
  n
      The length of the transform. If n is less than the input signal length,
      then x is truncated, if n is larger than x is zero-padded.
  norm
      The type of normalization to be applied. Must be either None or "ortho".
  out
      optional output array, for writing the result to.
  
  Returns
  -------
  ret
      Array containing the transformed input.
  
  Examples
  --------
  >>> x = ivy.array([8., 16., 24., 32., 40., 48., 56., 64.])
  >>> x.dct(type=2, norm="ortho")
  ivy.array([ 102.,  -51.5,   0.,  -5.39,   0.,  -1.61,   0., -0.406])
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code: def dct(
      self: ivy.Array,
      /,
      *,
      type: Literal[1, 2, 3, 4] = 2,
      n: Optional[int] = None,
      axis: int = -1,
      norm: Optional[Literal["ortho"]] = None,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance method variant of ivy.dct. This method simply
      wraps the function, and so the docstring for ivy.dct also applies to
      this method with minimal changes.
  
      Parameters
      ----------
      self
          The input signal.
      type
          The type of the dct. Must be 1, 2, 3 or 4.
      n
          The length of the transform. If n is less than the input signal length,
          then x is truncated, if n is larger than x is zero-padded.
      norm
          The type of normalization to be applied. Must be either None or "ortho".
      out
          optional output array, for writing the result to.
  
      Returns
      -------
      ret
          Array containing the transformed input.
  
      Examples
      --------
      >>> x = ivy.array([8., 16., 24., 32., 40., 48., 56., 64.])
      >>> x.dct(type=2, norm="ortho")
      ivy.array([ 102.,  -51.5,   0.,  -5.39,   0.,  -1.61,   0., -0.406])
      """
      return ivy.dct(
          self._data,
          type=type,
          n=n,
          axis=axis,
          norm=norm,
          out=out,
      )
  
imports: import abc
  from typing import Optional, Union, Tuple, List, Literal, Sequence, Callable
  import ivy
label_desc: Use image node_id 7 for calling the _ArrayWithLayersExperimental obj's underlying member method code with example usage: obj.dct() and returns: ivy